Address Usage Estimation Based on Bitcoin Traffic Behavior

Hiroki Matsumoto, Shusei Igaki, Hiroaki Kikuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper studies bitcoin address usage, which is assumed to be hidden via address pseudonyms. Transaction anonymity is ensured by means of bitcoin addresses, leading to abuse for illegitimate purposes, e.g., payments of illegal drugs, ransom, fraud, and money laundering. Although all the transactions are available in the bitcoin system, it is not trivial to determine the usage of addresses. This work aims to estimate typical usages of bitcoin transactions based on transaction features. With the decision tree learning algorithm, the proposed algorithm classifies a set of unknown addresses into seven classes; provider addresses of three services for mining pool, Bitcoin ATM, and dark websites; and user addresses of four services for mining Bitcoin ATM, dark websites, exchange, and a bulletin board system. The experimental results reveal some useful characteristics of bitcoin traffic, including statistics of frequency, amount of value, and significant transaction features.

Original languageEnglish
Title of host publicationAdvances in Networked-Based Information Systems - The 23rd International Conference on Network-Based Information Systems, NBiS 2020
EditorsLeonard Barolli, Kin Fun Li, Tomoya Enokido, Makoto Takizawa
PublisherSpringer
Pages188-199
Number of pages12
ISBN (Print)9783030578107
DOIs
Publication statusPublished - 2021
Event23rd International Conference on Network-Based Information Systems, NBiS 2020 - Victoria, Canada
Duration: 31 Aug 20202 Sep 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1264 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference23rd International Conference on Network-Based Information Systems, NBiS 2020
CountryCanada
CityVictoria
Period31/08/202/09/20

Fingerprint Dive into the research topics of 'Address Usage Estimation Based on Bitcoin Traffic Behavior'. Together they form a unique fingerprint.

Cite this